Large-scale wind power grid modelling and stability evaluation using stochastic approaches

Abstract

With the global demand to increase the level of low-carbon renewable energy resources (RERs) for electric power generation, dwindling fossil fuel reserves, and concerns that fossil fuel emissions are leading to climate change with possibly disastrous consequences, research is underway to discover the probable large-scale usage of RERs that will not be integrated into an existing power grid. A large-scale RER power grid is anticipated to run independently and be stable and dependable, like a traditional system. Wind power generation is no longer negligible. Wind energy is one of the most established renewable power options for ensuring RE self-sufficiency, but it's also one of the ficklest (RERs). Wind power generation is predicted to rise quickly in the next years owing to interest in renewable energy to counteract global warming. National or regional RE power networks are the subjects of growing study. The issue is the grid's stability and dependability. Wind farms' production variability, intermittency, and load mismatch can damage grid voltage stability. In answer to this difficulty, a large-scale wind power system was modeled using a stochastic methodology, and the results were analyzed using the Lyapunov technique, matrix exponential, and Hurwitz criteria to determine the future stability of a 100% RE grid.